Home Collections 11 Best + Free Computer Vision Courses & Certification Programs

11 Best + Free Computer Vision Courses & Certification Programs

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Computer vision is a subfield of Artificial intelligence that makes computing systems derive interpretable information and based on its assessments it provides valuable recommendations or otherwise takes actions of its own. Computer vision authorizes computers to observe and apprehend. The fundamental motive behind the invention of this field is that the data generated nowadays is enormous. There are hundreds of thousands of images shared every day online. As these images can comprise photos and videos so they can also carry data obtained from optical sensors or thermal sensors and other sources as well.

Computer vision is a replica of human vision but computer vision has to carry out all these functions quickly with algorithms. The major feature that surpasses human abilities is that it can detect minute and indistinguishable errors every second.

Statistics show that the market will keep growing and was expected to reach approximately USD 48.6 billion by 2022 and it proved to be of more worth than this by 2023.

# Course Name University/Organization Ratings Duration
1. Introduction to Computer Vision and Image Processing IBM ★★★★ 4.4 21 Hours
2. Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs Udemy ★★★★ 4.3 11 Hours
3. Convolutional Neural Networks DeepLearning.AI ★★★★★ 4.9 36 Hour
4. Computer Vision Executive Education Program Carnegie Mellon University 100 Hours
5. Become a Computer Vision Expert Udacity 180 Hours
6. Modern Computer Vision™ PyTorch, Tensorflow2 Keras & OpenCV4 Udemy ★★★★★ 4.5 28 Hours
7. Computer Vision for Engineering and Science Specialization MathWorks ★★★★★ 5.0 36 Hours
8. Python for Computer Vision with OpenCV and Deep Learning Udemy ★★★★★ 4.6 14 Hours
9. Python Project: pillow, tesseract, and opencv University of Michigan ★★★★ 4.0 19 Hours
10. Deep Learning: Advanced Computer Vision (GANs, SSD, +More!) Udemy ★★★★★ 4.7 16 Hours
11. Advanced Computer Vision with TensorFlow DeepLearning.AI ★★★★★ 4.8 19 Hours
In order to help our readers in taking a knowledgeable learning decision, TakeThisCourse.net has introduced a metric to measure the effectiveness of an online course. Learn more about how we measure an online course effectiveness.

Best + Free Computer Vision Courses & Certification Programs

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Introduction to Computer Vision and Image Processing

      • IBM via Coursera
      • 46,257+ already enrolled!
      • ★★★★☆ (928 Ratings)

Introduction to Computer Vision and Image Processing

Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Good
★★★★☆
Good
★★★★☆
Fair
★★★☆☆
Fair
★★★☆☆

This course explains the wide variety of applications of computer vision in industries and other governmental organizations, such as augmented reality, cancer detection, road conditioning monitoring, reading barcodes, product assembly, and many more. For image processing, this course teaches you to employ Pillow, Python, and others such as OpenCV.

  • The reason behind the selection of this course is that this course helps the participant in getting hands-on experience in object detection. Practical exercises and labs are also included in this course. Labs incorporate Jupyter and CV Studio.
  • This course is for beginners and a fresher willing to understand what computer vision is.
This course was the best in my judgment. I enjoyed it a lot and I want to convey my appreciation to the team that designed this course in a very professional and technically sound manner (SS, ★★★★★)

Coursera Plus Courses

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Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs

      • Hadelin de Ponteves via Udemy
      • 46,842+ already enrolled!
      • ★★★★☆ (6,447 Ratings)

Deep Learning and Computer Vision A-Z

Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Excellent
★★★★★
Fair
★★★☆☆
Good
★★★★☆
Good
★★★★☆

This course not only provides knowledge regarding computer vision and how to use it but also allows maximizing its utilization.

  • The reason why we chose this course is that the core objective of the course is to help the participants not only understand how the most popular computer vision methods work but also to learn and apply them practically.
  • This course is for every individual looking to develop an insight into computer vision.
Some parts of the course had just an overview of that section but it was more than enough to get an understanding of the subject. GANs section was amazing. I was able to run the code on my own. (Alex F, ★★★★★)

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Convolutional Neural Networks

      • DeepLearning.AI via Coursera
      • 452,445+ already enrolled!
      • ★★★★★ (41,406 Ratings)

Convolutional Neural Networks

Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Excellent
★★★★★
Good
★★★★☆
Good
★★★★☆
Fair
★★★☆☆

In this course, you will learn how to develop a convolutional neural network. This course also teaches you about residual networks, integration of the convolutional network with visual detection and recognition tasks, production and deployment of these algorithms to process 2D or 3D A/V data, and much more.

  • This course is selected because in this course, apart from technical development, you will also get insights into the challenges and ramifications of deep learning to help you develop your skills according to advanced AI tech. This course not only helps you to enhance your knowledge and skills but also to apply it at your workplace and give a boost to your career.
  • This course is for those aspirants who aim to learn convolutional networks in particular and concepts related to them.
The ideas and insights developed in this course are unmatchable. The extensive knowledge related to CNN. In terms of my experience, I haven’t gone through any better courses than this in the MOOC world. (RK, ★★★★★)

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Computer Vision Executive Education Program

      • via Carnegie Mellon University
      • 100 Hours of effort required!
      • Study Type: Self-paced

Computer Vision

Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Good
★★★★☆
Fair
★★★☆☆
Fair
★★★☆☆
Fair
★★★☆☆

In this extensive training comprised of 10 perfectly designed modules, you will learn about Core image processing methods and understand the multiple techniques incorporated in them. Also, Image detection and objection recognition by using neural networks, Fundamental knowledge about geometrical visions and deriving useful 3D information out of those images, Useful techniques used in the alignment of objects in a video, and much more.

  • The sole reason for choosing this course is its practical applicability and the rich content offered in it.
  • This program is viable for those who have prior experience in Python and advanced calculus and linear algebra (ACLA). Also, this course will prove to be useful for those who are willing to give their career a thrust by acquiring a certification from a renowned school.

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Become a Computer Vision Expert

      • via Udacity
      • 180 Hours of effort required!
      • Study Type: Self-paced
Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Excellent
★★★★★
Good
★★★★☆
Good
★★★★☆
Good
★★★★☆

This course offers leading-edge computer vision and DL techniques. This course will start with fundamental image processing and take you to the complexities of developing and customizing convolutional neural networks.

  • The reason why we chose this course is that this course gives a career-boosting skill that makes your resume more professional. Concepts related to object tracking and facial recognition are a few of the many key take-away of the course.
  • This course is an advanced version, so this course is best suited for those individuals who possess Prior knowledge of Python from the intermediate level to a bit above, have moderate information regarding statistics, especially probability, have Intermediate knowledge of ML techniques, and have been involved in working basic neural networks.
At first, I was a bit cautious but as the course progressed I was amazed to see that his course ver-well organized and more practical way. This course promoted the mini-projects that helped me achieve hands-on experience. I gained very thorough insights during the course. (Muhammad Sulaiman N, ★★★★★)

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Modern Computer Vision™ PyTorch, Tensorflow2 Keras & OpenCV4

      • Rajeev D. Ratan via Udemy
      • 9,091+ already enrolled!
      • ★★★★★ (980 Ratings)

Modern Computer Vision™ PyTorch, Tensorflow2 Keras & OpenCV4

Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Good
★★★★☆
Good
★★★★☆
Good
★★★★☆
Fair
★★★☆☆

This course offers foundational knowledge related to computer vision using OpenCV followed by concepts of deep learning (DL). Also, this course includes concepts like Graphics control and operation, Facial recognition and object detection,2D and 3D image illustrations, and much more

  • The reason that brought about the selection of the course is the engaging nature of the course.
  • This course covers a wide spectrum of participants from software developers to high school students looking to get a kick start in computer vision.
The main attraction of the course is the blend of advanced ML methods with classical methods. Even beginners can cope with it easily.

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Computer Vision for Engineering and Science Specialization

      • MathWorks via Coursera
      • 36 Hours of effort required!
      • ★★★★★ (08 Ratings)

Computer Vision for Engineering and Science Specialization

Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Good
★★★★☆
Good
★★★★☆
Good
★★★★☆
Fair
★★★☆☆

This course offers top-notch skills that are in demand right now. In this course, you will carry out different projects involving object detection, acquire skillful training in models of image classification, learn methods for image alignment and tracking of objects, and much more.

  • The reason why we chose this course is that it offers advanced knowledge on specialized topics related to computer vision.
  • This course is for those individuals who aspire to acquire expertise in computer vision but should have prior experience related to image processing.
Coursera helps me to achieve my objective to learn great skills. (Harry S)

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Python for Computer Vision with OpenCV and Deep Learning

      • Jose Portilla via Udemy
      • 50,983+ already enrolled!
      • ★★★★★ (9,343 Ratings)

Python for Computer Vision with OpenCV and Deep Learning

Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Good
★★★★☆
Good
★★★★☆
Fair
★★★☆☆
Fair
★★★☆☆

In this course, you will learn how to integrate Python with Computer vision to process Audio/visual data. NumPy library is the most appropriate to use for numerical processing, so this course will teach you how to extract and manipulate image data. Participants will also get the opportunity to learn the OpenCV library for image opening and basics. Modern DL topics that include custom image classification and image recognition followed by YOLO are also included in this course.

  • This course is selected because it provides great skills which are in demand in the market.
  • Python beginners may find difficulty in coping with the course. This course is well-suited for Python developers.
The lessons were well-designed and the quality of the practical work was amazing. (Farnoush A)

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Python Project: pillow, tesseract, and opencv

      • University of Michigan via Coursera
      • 62,693+ already enrolled!
      • ★★★★☆ (1,810 Ratings)
Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Excellent
★★★★★
Good
★★★★☆
Good
★★★★☆
Fair
★★★☆☆

In this course you will learn the use of Pillow (Pyhton image library) for image manipulations, the use of Tesseract and  Py-tesseract for optical detection and recognition of text, the use of OpenCV for facial and object detection plus recognition, developing Data analysis project of the data obtained from live sources using the aforementioned libraries.

  • The reason why we chose this course is that it offers rich content which has greater applicability.
  • This course is the best compliment for those participants who are already aware of Python programming skills and aspiring to gain hands-on experience and improve practical knowledge.
This course is a bit challenging yet it carves out the best in you. Amazing course for computer vision learners. (JS)

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Deep Learning: Advanced Computer Vision (GANs, SSD, +More!)

      • Lazy Programmer Inc. via Udemy
      • 34,146+ already enrolled!
      • ★★★★★ (5,401 Ratings)

Deep Learning- Advanced Computer Vision (GANs, SSD, +More!)

Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Good
★★★★☆
Good
★★★★☆
Good
★★★★☆
Fair
★★★☆☆

In this course you will learn the Conversion of a CNN into an object detection system, the Use of SSD algorithm having more accuracy than the previous one, the Understanding of neural style transfer, the Combining content image and style image, the Use of GAN for the development, Use of object localization for the detection of objects.

  • The reason which brought about the selection of this course is that it offers perfect integration of basic CNN architecture with advanced and new architectures such as VGG and Inception. This has high market demand.
  • This course is a perfect fit even for beginners but must who have prior basic knowledge of mathematical concepts.
This course is worthy enough even for beginners to deep learning and programming but must have basic mathematical concepts. This course considers the easy-to-follow approach which is the key attraction to the course. (Amrit K)

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Advanced Computer Vision with TensorFlow

      • DeepLearning.AI via Coursera
      • 25,994+ already enrolled!
      • ★★★★★ (409 Ratings)

Advanced Computer Vision with TensorFlow

Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Good
★★★★☆
Good
★★★★☆
Good
★★★★☆
Fair
★★★☆☆

In this course you will learn about object detection and recognition, building your models for the detection, localization, and manipulation of the image, the Use of FCN and its variations and complexities, and Advanced ML techniques including saliency maps and class activation maps

  • The reason why we chose this course is that it helps the participants to develop skills that have high practical usage in the workplace.
  • This course is for beginners as well as intermediate-level ML professionals looking to improve their knowledge of TensorFlow.
The course content was well-designed. I learned the concepts with proper practical illustrations. It is a very productive course. (Jennifer J)

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